【作者】 李伟；

【导师】 胡小建；

【作者基本信息】 合肥工业大学 ， 管理科学与工程， 2020， 硕士

【摘要】 随着互联网云计算技术的发展,“互联网+”高效物流被提出,物流行业逐渐信息化、平台化,对于效率、效益的竞争愈加激烈。云物流平台利用现代信息技术,摆脱了传统的物流模式,可以智能制定物流计划,改进业务流程,充分利用有限资源,提高企业效率效益和竞争力。利用物流系统的资源共享、信息互通,进而充分利用运力资源,整合社会运力,通过计算机智能地制定调度计划,解决运力资源的合理调度是当前的关键问题。这个问题的研究对于加快云物流平台建设,提高了运输过程的效率,促进了物流成本的降低,以及我国物流业的资源整合与“互联网+”环境下的物流业发展都具有重要意义。本文基于云物流及其大数据服务关键技术研究与产业项目,根据云物流平台现有建设水平提供运力调度解决方案。云物流平台下的运力调度包括提货调度与干线运输调度两个问题,文中考虑了运输的成本、时间成本、车辆满载率、多车型、多集散中心、甩挂运输模式、动态大规模信息等一系列云物流平台下的重要影响因素,分别提出多目标运力调度模型求解这两个问题。针对提货运力调度问题,本文使用了两阶段解决策略求解多集散中心调度模型,使用KNN聚类和遗传算法求解模型得到运力调度方案,结果表明在降低成本和提高运力资源利用率以及响应时间方面都有较大改善,证明了模型的有效性;针对干线运输运力调度问题,本文结合实际考虑了甩挂运输模式,提出调度闲置车辆以充分利用运力,并使用遗传算法求解模型得到调度方案,结果表明模型具有良好的优化效果,能够加强对运输成本和运输时间的控制。本文提出的运力调度模型都是源自于云物流平台物流环节中的实际问题,对于加快云物流平台的建设促进互联网时代下物流业的发展具有积极意义。更多还原

【Abstract】 With the development of Internet cloud computing technology,"Internet plus" efficient logistics has been put forward.The logistics industry is becoming more and more information-based and platform-based,and the competition for efficiency and efficiency is becoming increasingly fierce.Cloud logistics platform uses modern information technology to get rid of the traditional logistics mode.It can intelligently make logistics plans,improve business processes,make full use of limited resources,and improve the efficiency,efficiency and competitiveness of enterprises.Using the resource sharing and information exchange of logistics system,making full use of transportation resources,integrating social transportation capacity,making intelligent scheduling plan through computer,and solving the reasonable scheduling of transportation resources are the key problems at present.The research of this issue is of great significance for accelerating the construction of cloud logistics platform,improving the efficiency of transport process,promoting the reduction of logistics cost,and integrating resources in China’s logistics industry and developing logistics industry under the "Internet plus" environment.Based on the key technology research and industrial projects of cloud logistics and its big data service,this paper provides a solution of capacity scheduling for the existing construction level of cloud logistics platform.This paper makes an in-depth study on the process of picking up and trunk transportation scheduling in the cloud logistics platform mode,considering a series of important factors under the cloud logistics platform,such as the transportation cost,time cost,vehicle full load rate,multiple models,multiple distribution centers,drop and hang transportation mode,dynamic large-scale information,and puts forward a multi-objective transportation capacity scheduling model for picking up and trunk respectively.In the model of picking up capacity scheduling,this paper uses two-stage solution strategy to solve the multi distribution center scheduling problem,and uses KNN clustering and genetic algorithm to solve the model to get the capacity scheduling scheme.The results show that there are great improvements in reducing costs and improving the utilization rate of capacity resources and response time,which proves the effectiveness of the model.In the transportation capacity scheduling model of trunk line,this paper considers the throw and hang transportation mode in combination with the actual situation,proposes to schedule idle vehicles to make full use of the transportation capacity,and uses genetic algorithm to solve the model to get the scheduling scheme,the results show that the model has good optimization effect,and can strengthen the control of transportation cost and transportation time.The transportation capacity scheduling models proposed in this paper are all derived from the practical problems in the logistics link of the cloud logistics platform,which has a positive significance for accelerating the construction of the cloud logistics platform and promoting the development of the logistics industry in the Internet era.更多还原